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Infinite dimensional compressed sensing from anisotropic measurements and applications to inverse problems in PDE. (arXiv:1710.11093v2 [cs.IT] UPDATED)
来源于:arXiv
We consider a compressed sensing problem in which both the measurement and
the sparsifying systems are assumed to be frames (not necessarily tight) of the
underlying Hilbert space of signals, which may be finite or infinite
dimensional. The main result gives explicit bounds on the number of
measurements in order to achieve stable recovery, which depends on the mutual
coherence of the two systems. As a simple corollary, we prove the efficiency of
nonuniform sampling strategies in cases when the two systems are not
incoherent, but only asymptotically incoherent, as with the recovery of wavelet
coefficients from Fourier samples. This general framework finds applications to
inverse problems in partial differential equations, where the standard
assumptions of compressed sensing are often not satisfied. Several examples are
discussed, with a special focus on electrical impedance tomography. 查看全文>>